Research on Fighter Air Combat Effectiveness Evaluation Based on RVM and KFDA

In order to evaluate reasonably the fighter air combat effectiveness, a Relevance Vector Machine (RVM) effectiveness evaluation method is proposed based on Kernel Fisher Discriminant Analysis (KFDA) feature extraction. Firstly, on the basis of system analysis, the index system of effectiveness evaluation of fighter air combat is introduced, then KFDA is used to extract higher-order nonlinear features from evaluation index data, finally the advantages of RVM in nonlinear system modeling are applied to establish the effectiveness evaluation model of fighter air combat based on extracted features and complete the effectiveness evaluation. The actual example shows that, the root mean square error obtained by proposed method can achieve 0.0094 for effectiveness evaluation of fighter air combat. It has a scientific and reasonable process and an accurate evaluation result. This verifies its feasible and effective in effectiveness evaluation of fighter air combat.